Path Planning with A* and RRT | Autonomous Navigation, Part 4

See the other videos in this series: https://www.youtube.com/playlist?list=PLn8PRpmsu08rLRGrnF-S6TyGrmcA2X7kg

This video explores some of the ways that we can use a map like a binary occupancy grid for motion and path planning. We briefly cover what motion planning means and how we can use a graph to solve this planning problem. We then walk through two popular approaches for creating that graph: search-based algorithms like A* and sampling-based algorithms like RRT and RRT*.

Additional Resources:
- Planning Mobile-Robot Paths Using RRT MATLAB: https://bit.ly/38PsPZb
- Create an RRT planner: https://bit.ly/2Zoyjac
- Download ebook: Sensor Fusion and Tracking for Autonomous Systems: An Overview: https://bit.ly/32iVFzX
- Download white paper: Sensor Fusion and Tracking for Autonomous Systems: https://bit.ly/2DwbHvK
- Sampling-Based Algorithms for Optimal Motion Planning, Karaman and Frazzoli: https://arxiv.org/pdf/1105.1186.pdf
- A* Path Finding by Sebastian Lague video: https://youtu.be/-L-WgKMFuhE
- RRT, RRT* & Random Trees by Aaron Becker video: https://www.youtube.com/watch?v=Ob3BIJkQJEw
- RRT* FND: Motion Planning in Dynamic Environments video: https://www.youtube.com/watch?v=hXTnWN8NiKE

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